{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"papermill": {
"duration": 0.35409,
"end_time": "2020-03-13T17:04:15.061697",
"exception": false,
"start_time": "2020-03-13T17:04:14.707607",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import os\n",
"from IPython.display import display, HTML, Markdown"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"papermill": {
"duration": 0.02437,
"end_time": "2020-03-13T17:04:15.106586",
"exception": false,
"start_time": "2020-03-13T17:04:15.082216",
"status": "completed"
},
"tags": [
"parameters"
]
},
"outputs": [],
"source": [
"ts_folder = \"../data/covid-19_jhu-csse/\"\n",
"rates_folder = \"../data/covid-19_rates/\"\n",
"out_folder = None\n",
"PAPERMILL_OUTPUT_PATH = None"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"papermill": {
"duration": 0.022646,
"end_time": "2020-03-13T17:04:15.137496",
"exception": false,
"start_time": "2020-03-13T17:04:15.114850",
"status": "completed"
},
"tags": [
"injected-parameters"
]
},
"outputs": [],
"source": [
"# Parameters\n",
"PAPERMILL_INPUT_PATH = \"notebooks/Dashboard.ipynb\"\n",
"PAPERMILL_OUTPUT_PATH = \"runs/Dashboard.run.ipynb\"\n",
"ts_folder = \"./data/covid-19_jhu-csse/\"\n",
"rates_folder = \"./data/covid-19_rates/\"\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"papermill": {
"duration": 0.021072,
"end_time": "2020-03-13T17:04:15.168525",
"exception": false,
"start_time": "2020-03-13T17:04:15.147453",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"# Read in the data"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"papermill": {
"duration": 0.065756,
"end_time": "2020-03-13T17:04:15.243131",
"exception": false,
"start_time": "2020-03-13T17:04:15.177375",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"def read_jhu_covid_df(name):\n",
" filename = os.path.join(ts_folder, f\"time_series_19-covid-{name}.csv\")\n",
" df = pd.read_csv(filename)\n",
" df = df.set_index(['Province/State', 'Country/Region', 'Lat', 'Long'])\n",
" df.columns = pd.to_datetime(df.columns)\n",
" return df\n",
"\n",
"\n",
"jhu_frames_map = {\n",
" \"confirmed\": read_jhu_covid_df(\"Confirmed\"),\n",
" \"deaths\": read_jhu_covid_df(\"Deaths\"),\n",
" \"recovered\": read_jhu_covid_df(\"Recovered\")\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"papermill": {
"duration": 0.038039,
"end_time": "2020-03-13T17:04:15.289236",
"exception": false,
"start_time": "2020-03-13T17:04:15.251197",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"def read_rates_covid_df(name):\n",
" filename = os.path.join(rates_folder, f\"ts_rates_19-covid-{name}.csv\")\n",
" df = pd.read_csv(filename).drop(\"Unnamed: 0\", axis=1)\n",
" df = df.set_index(['Country/Region'])\n",
" df.columns = pd.to_datetime(df.columns)\n",
" return df\n",
"\n",
"\n",
"rates_frames_map = {\n",
" \"confirmed\": read_rates_covid_df(\"confirmed\"),\n",
" \"deaths\": read_rates_covid_df(\"deaths\"),\n",
" \"recovered\": read_rates_covid_df(\"recovered\")\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"papermill": {
"duration": 0.017688,
"end_time": "2020-03-13T17:04:15.314301",
"exception": false,
"start_time": "2020-03-13T17:04:15.296613",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"# Compile data needed for the visualizations"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"papermill": {
"duration": 0.040604,
"end_time": "2020-03-13T17:04:15.374996",
"exception": false,
"start_time": "2020-03-13T17:04:15.334392",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"# Compute geospatial coordinates\n",
"country_coords_df = jhu_frames_map['confirmed'].reset_index([2,3])[['Lat', 'Long']]\n",
"country_coords_df = country_coords_df.groupby(level='Country/Region').mean()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"papermill": {
"duration": 0.034326,
"end_time": "2020-03-13T17:04:15.424734",
"exception": false,
"start_time": "2020-03-13T17:04:15.390408",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"# Identify countries with 100 or more cases\n",
"case_count_ser = jhu_frames_map['confirmed'].iloc[:,-1].groupby(level='Country/Region').sum()\n",
"countries_over_thresh = case_count_ser[case_count_ser > 99].index"
]
},
{
"cell_type": "markdown",
"metadata": {
"papermill": {
"duration": 0.009134,
"end_time": "2020-03-13T17:04:15.448316",
"exception": false,
"start_time": "2020-03-13T17:04:15.439182",
"status": "completed"
},
"tags": []
},
"source": [
"# Questions About COVID-19 and Its Spread\n",
"\n",
"These plots should be taken with a large grain of salt. I am not an epidemiologist, so the analyses shown here are completely naive. There are large discrepencies in the data from different countries for a variety of reasons (rates of testing, demographics, etc.) so that make direct comparisons inaccurate. Nonetheless, I think there is a lot of interesting information in this data."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"papermill": {
"duration": 0.041449,
"end_time": "2020-03-13T17:04:15.498158",
"exception": false,
"start_time": "2020-03-13T17:04:15.456709",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<em>Data up to Mar 10 2020</em>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_ts = jhu_frames_map['confirmed'].iloc[:,-1].name.strftime(\"%b %d %Y\")\n",
"display(HTML(f\"<em>Data up to {data_ts}</em>\"))"
]
},
{
"cell_type": "markdown",
"metadata": {
"papermill": {
"duration": 0.009938,
"end_time": "2020-03-13T17:04:15.526404",
"exception": false,
"start_time": "2020-03-13T17:04:15.516466",
"status": "completed"
},
"tags": []
},
"source": [
"## How are cases per 100,000 distributed geographically?"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"papermill": {
"duration": 0.199352,
"end_time": "2020-03-13T17:04:15.733984",
"exception": false,
"start_time": "2020-03-13T17:04:15.534632",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"import altair as alt\n",
"from vega_datasets import data"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"papermill": {
"duration": 0.045428,
"end_time": "2020-03-13T17:04:15.799713",
"exception": false,
"start_time": "2020-03-13T17:04:15.754285",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"# Compile the basic df\n",
"map_df = pd.concat([\n",
" rates_frames_map['confirmed'].iloc[:,-1],\n",
" rates_frames_map['deaths'].iloc[:,-1],\n",
" rates_frames_map['recovered'].iloc[:,-1],\n",
" country_coords_df], axis=1)\n",
"# Restrict to countries with 100 or more cases\n",
"map_df = map_df.loc[countries_over_thresh].dropna()\n",
"map_df = map_df.reset_index()\n",
"map_df.columns = ['Country/Region', 'Confirmed', 'Deaths', 'Recovered', 'Lat', 'Long']"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"papermill": {
"duration": 0.030132,
"end_time": "2020-03-13T17:04:15.844929",
"exception": false,
"start_time": "2020-03-13T17:04:15.814797",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"def map_of_variable(map_df, variable):\n",
" # Data generators for the background\n",
" sphere = alt.sphere()\n",
" graticule = alt.graticule()\n",
"\n",
" # Source of land data\n",
" source = alt.topo_feature(data.world_110m.url, 'countries')\n",
"\n",
" # Layering and configuring the components\n",
" p = alt.layer(\n",
" alt.Chart(sphere).mark_geoshape(fill='#cae6ef'),\n",
" alt.Chart(graticule).mark_geoshape(stroke='white', strokeWidth=0.5),\n",
" alt.Chart(source).mark_geoshape(fill='#dddddd', stroke='#aaaaaa'),\n",
" alt.Chart(map_df).mark_circle(opacity=0.6).encode(\n",
" longitude='Long:Q',\n",
" latitude='Lat:Q',\n",
" size=alt.Size(f'{variable}:Q', title=\"Cases\"),\n",
" color=alt.value('steelblue'),\n",
" tooltip=[\"Country/Region:N\", \"Confirmed:Q\", \"Deaths:Q\", \"Recovered:Q\"]\n",
" )\n",
" ).project(\n",
" 'naturalEarth1'\n",
" ).properties(width=600, height=400, title=f\"{variable} cases per 100,000\"\n",
" ).configure_view(stroke=None)\n",
" return p"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"papermill": {
"duration": 0.100208,
"end_time": "2020-03-13T17:04:15.958509",
"exception": false,
"start_time": "2020-03-13T17:04:15.858301",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"data": {
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" (function(spec, embedOpt){\n",
" const outputDiv = document.getElementById(\"altair-viz-b79eb79d0e8f4b50be1688903bb8f9f0\");\n",
" const paths = {\n",
" \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
" \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
" \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n",
" \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
" };\n",
"\n",
" function loadScript(lib) {\n",
" return new Promise(function(resolve, reject) {\n",
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" s.src = paths[lib];\n",
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" throw err;\n",
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" function displayChart(vegaEmbed) {\n",
" vegaEmbed(outputDiv, spec, embedOpt)\n",
" .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
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"\n",
" if(typeof define === \"function\" && define.amd) {\n",
" requirejs.config({paths});\n",
" require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
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"</script>"
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"alt.LayerChart(...)"
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"data": {
"text/html": [
"\n",
"<p style=\"font-size: smaller\">Data Source: \n",
" <a href=\"https://github.com/CSSEGISandData/COVID-19\">JHU CSSE</a> and\n",
" <a href=\"https://data.worldbank.org/indicator/SP.POP.TOTL\">World Bank</a>\n",
"</p>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"display(map_of_variable(map_df, 'Confirmed'))\n",
"display(HTML('''\n",
"<p style=\"font-size: smaller\">Data Source: \n",
" <a href=\"https://github.com/CSSEGISandData/COVID-19\">JHU CSSE</a> and\n",
" <a href=\"https://data.worldbank.org/indicator/SP.POP.TOTL\">World Bank</a>\n",
"</p>'''))"
]
},
{
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"metadata": {
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"duration": 0.062654,
"end_time": "2020-03-13T17:04:16.037936",
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"status": "completed"
},
"tags": []
},
"outputs": [
{
"data": {
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" const paths = {\n",
" \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
" \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
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" .then(() => displayChart(vegaEmbed));\n",
" }\n",
" })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"Confirmed\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Country/Region\", \"sort\": \"-x\"}}}, {\"mark\": {\"type\": \"text\", \"align\": \"left\", \"baseline\": \"middle\", \"dx\": 3}, \"encoding\": {\"text\": {\"type\": \"quantitative\", \"field\": \"Confirmed\", \"format\": \".3\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"Confirmed\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Country/Region\", \"sort\": \"-x\"}}}], \"data\": {\"name\": \"data-433f706ddfa6221156e78c265aebad1f\"}, \"height\": 900, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.0.2.json\", \"datasets\": {\"data-433f706ddfa6221156e78c265aebad1f\": [{\"Country/Region\": \"Australia\", \"Confirmed\": 0.4281306826095598, \"Deaths\": 0.012003663998398872, \"Recovered\": 0.0840256479887921, \"Lat\": -23.1315375, \"Long\": 140.0609875}, {\"Country/Region\": \"Austria\", \"Confirmed\": 2.057185925638154, \"Deaths\": 0.0, \"Recovered\": 0.04521287748655284, \"Lat\": 47.5162, \"Long\": 14.5501}, {\"Country/Region\": \"Bahrain\", \"Confirmed\": 7.00887387149166, \"Deaths\": 0.0, \"Recovered\": 1.4017747742983322, \"Lat\": 26.0275, \"Long\": 50.55}, {\"Country/Region\": \"Belgium\", \"Confirmed\": 2.3375802000128174, \"Deaths\": 0.0, \"Recovered\": 0.008754982022519914, \"Lat\": 50.8333, \"Long\": 4.0}, {\"Country/Region\": \"Denmark\", \"Confirmed\": 4.519231399481772, \"Deaths\": 0.0, \"Recovered\": 0.01724897480718234, \"Lat\": 56.2639, \"Long\": 9.5018}, {\"Country/Region\": \"France\", \"Confirmed\": 2.663193607427707, \"Deaths\": 0.04926311045129727, \"Recovered\": 0.017913858345926282, \"Lat\": 47.0, \"Long\": 2.0}, {\"Country/Region\": \"Germany\", \"Confirmed\": 1.7569474368355689, \"Deaths\": 0.0024117329263357162, \"Recovered\": 0.021705596337021446, \"Lat\": 51.0, \"Long\": 9.0}, {\"Country/Region\": \"Hong Kong SAR\", \"Confirmed\": 1.61052207757348, \"Deaths\": 0.040263051939337005, \"Recovered\": 0.8723661253523016, \"Lat\": 22.3, \"Long\": 114.2}, {\"Country/Region\": \"Iran (Islamic Republic of)\", \"Confirmed\": 9.831263513326588, \"Deaths\": 0.3557445514023921, \"Recovered\": 3.3386198277660917, \"Lat\": 32.0, \"Long\": 53.0}, {\"Country/Region\": \"Italy\", \"Confirmed\": 16.794281862259982, \"Deaths\": 1.0441611838689575, \"Recovered\": 1.198054987513669, \"Lat\": 43.0, \"Long\": 12.0}, {\"Country/Region\": \"Japan\", \"Confirmed\": 0.4591829073311989, \"Deaths\": 0.007903320263876057, \"Recovered\": 0.07982353466514817, \"Lat\": 36.0, \"Long\": 138.0}, {\"Country/Region\": \"Mainland China\", \"Confirmed\": 5.798467757569664, \"Deaths\": 0.2251692718617392, \"Recovered\": 4.315696509732684, \"Lat\": 33.40693612903227, \"Long\": 111.54290322580646}, {\"Country/Region\": \"Malaysia\", \"Confirmed\": 0.4091525198482584, \"Deaths\": 0.0, \"Recovered\": 0.07612139904153642, \"Lat\": 2.5, \"Long\": 112.5}, {\"Country/Region\": \"Netherlands\", \"Confirmed\": 2.216932407413909, \"Deaths\": 0.02321395191009329, \"Recovered\": 0.0, \"Lat\": 52.1326, \"Long\": 5.2913}, {\"Country/Region\": \"Norway\", \"Confirmed\": 7.526810498997428, \"Deaths\": 0.0, \"Recovered\": 0.018817026247493568, \"Lat\": 60.472, \"Long\": 8.4689}, {\"Country/Region\": \"Republic of Korea\", \"Confirmed\": 14.550136054326911, \"Deaths\": 0.10457970809711876, \"Recovered\": 0.4783553314812655, \"Lat\": 36.0, \"Long\": 128.0}, {\"Country/Region\": \"Singapore\", \"Confirmed\": 2.837545551473431, \"Deaths\": 0.0, \"Recovered\": 1.3833034563432978, \"Lat\": 1.2833, \"Long\": 103.8333}, {\"Country/Region\": \"Spain\", \"Confirmed\": 3.6277054737195855, \"Deaths\": 0.07490837261367876, \"Recovered\": 0.06848765496107773, \"Lat\": 40.0, \"Long\": -4.0}, {\"Country/Region\": \"Sweden\", \"Confirmed\": 3.4861425832316537, \"Deaths\": 0.0, \"Recovered\": 0.009820119952765223, \"Lat\": 63.0, \"Long\": 16.0}, {\"Country/Region\": \"Switzerland\", \"Confirmed\": 5.7652500550986465, \"Deaths\": 0.035225560418118015, \"Recovered\": 0.035225560418118015, \"Lat\": 46.8182, \"Long\": 8.2275}, {\"Country/Region\": \"UK\", \"Confirmed\": 0.5745312032182892, \"Deaths\": 0.009024050312329149, \"Recovered\": 0.027072150936987446, \"Lat\": 55.0, \"Long\": -3.0}, {\"Country/Region\": \"US\", \"Confirmed\": 0.5104420019995022, \"Deaths\": 0.017116618031121033, \"Recovered\": 0.004584808401193134, \"Lat\": 38.77302746113991, \"Long\": -93.61047823834195}]}}, {\"mode\": \"vega-lite\"});\n",
"</script>"
],
"text/plain": [
"alt.LayerChart(...)"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bars = alt.Chart(map_df).mark_bar().encode(\n",
" x='Confirmed:Q',\n",
" y=alt.Y(\"Country/Region:N\", sort='-x')\n",
")\n",
"\n",
"text = bars.mark_text(\n",
" align='left',\n",
" baseline='middle',\n",
" dx=3 # Nudges text to right so it doesn't appear on top of the bar\n",
").encode(\n",
" text=alt.Text('Confirmed:Q', format=\".3\")\n",
")\n",
"\n",
"(bars + text).properties(height=900)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
},
"papermill": {
"duration": 2.520956,
"end_time": "2020-03-13T17:04:16.371464",
"environment_variables": {},
"exception": null,
"input_path": "notebooks/Dashboard.ipynb",
"output_path": "runs/Dashboard.run.ipynb",
"parameters": {
"PAPERMILL_INPUT_PATH": "notebooks/Dashboard.ipynb",
"PAPERMILL_OUTPUT_PATH": "runs/Dashboard.run.ipynb",
"rates_folder": "./data/covid-19_rates/",
"ts_folder": "./data/covid-19_jhu-csse/"
},
"start_time": "2020-03-13T17:04:13.850508",
"version": "1.1.0"
}
},
"nbformat": 4,
"nbformat_minor": 4
}